{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "079a580a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "from keras.layers import LSTM,Dropout\n",
    "import pandas as pd\n",
    "import os\n",
    "from keras.models import Sequential, load_model\n",
    "import tensorflow as tf\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "import matplotlib.pyplot as plt\n",
    "#支持中文\n",
    "from matplotlib import rcParams\n",
    "config = {\n",
    "    \"font.family\":'Times New Roman',  # 设置字体类型\n",
    "    \"font.size\": 12,\n",
    "#     \"mathtext.fontset\":'stix',\n",
    "}\n",
    "rcParams.update(config)\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "from sklearn.metrics import r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f6e90ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"数据(1).csv\",encoding = 'gb2312').iloc[:,:4]\n",
    "data['time'] = pd.to_datetime(data['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3aa2d58e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>新能源汽车销量</th>\n",
       "      <th>纯电动汽车销量</th>\n",
       "      <th>插电混动汽车销量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>5682</td>\n",
       "      <td>4978</td>\n",
       "      <td>704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>17596</td>\n",
       "      <td>13919</td>\n",
       "      <td>3677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-03-01</td>\n",
       "      <td>31120</td>\n",
       "      <td>25342</td>\n",
       "      <td>5778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-04-01</td>\n",
       "      <td>34361</td>\n",
       "      <td>28570</td>\n",
       "      <td>5791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>45000</td>\n",
       "      <td>38530</td>\n",
       "      <td>6770</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        time  新能源汽车销量  纯电动汽车销量  插电混动汽车销量\n",
       "0 2017-01-01     5682     4978       704\n",
       "1 2017-02-01    17596    13919      3677\n",
       "2 2017-03-01    31120    25342      5778\n",
       "3 2017-04-01    34361    28570      5791\n",
       "4 2017-05-01    45000    38530      6770"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "26942ec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcar = data[['新能源汽车销量','time']].set_index(\"time\")\n",
    "elecar = data[['纯电动汽车销量','time']].set_index(\"time\")\n",
    "blendcar = data[['插电混动汽车销量','time']].set_index(\"time\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "39fe842c",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcar['新能源汽车销量'].name=\"Sales of new energy vehicles\"\n",
    "elecar['纯电动汽车销量'].name = \"Sales of pure electric vehicles\"\n",
    "blendcar['插电混动汽车销量'].name = \"Sales of plug-in hybrid vehicles\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e428b8a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='time'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newcar['新能源汽车销量'].plot(legend=\"Sales of new energy vehicles\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d46670fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='time'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "elecar['纯电动汽车销量'].plot(legend=\"Sales of pure electric vehicles\",color=\"g\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2583c38d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='time'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "blendcar['插电混动汽车销量'].plot(legend=\"Sales of plug-in hybrid vehicles\",color=\"r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e60711f",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcar_dataframe = newcar['新能源汽车销量']\n",
    "newcar_dataset = newcar_dataframe.values\n",
    "\n",
    "elecar_dataframe = elecar['纯电动汽车销量']\n",
    "elecar_dataset = elecar_dataframe.values \n",
    "\n",
    "blendcar_dataframe = blendcar['插电混动汽车销量']\n",
    "blendcar_dataset = blendcar_dataframe.values \n",
    "all_result = np.append(np.append(newcar_dataset, elecar_dataset),blendcar_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9e308924",
   "metadata": {},
   "outputs": [],
   "source": [
    "## 数据归一化\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "result = scaler.fit_transform(all_result.reshape(-1,1))\n",
    "newcar_trainlist =  result[:72]\n",
    "elecar_trainlist =  result[72:144]\n",
    "blendcar_trainlist =  result[144:216]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a925962c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 对数据进行处理\n",
    "def create_dataset(dataset, look_back):\n",
    "#这里的look_back与timestep相同\n",
    "    dataX, dataY = [], []\n",
    "    for i in range(len(dataset)-look_back-1):\n",
    "        a = dataset[i:(i+look_back)]\n",
    "        dataX.append(a)\n",
    "        dataY.append(dataset[i + look_back])\n",
    "    return np.array(dataX),np.array(dataY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3e4f4d27",
   "metadata": {},
   "outputs": [],
   "source": [
    "#训练数据太少 look_back并不能过大\n",
    "look_back =1\n",
    "\n",
    "newcar_trainX,newcar_trainY  = create_dataset(newcar_trainlist,look_back)\n",
    "elecar_trainX,elecar_trainY  = create_dataset(elecar_trainlist,look_back)\n",
    "blendcar_trainX,blendcar_trainY  = create_dataset(blendcar_trainlist,look_back)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4d4bfc3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_model(trainX, trainY):\n",
    "    trainX = np.reshape(trainX, (trainX.shape[0], trainX.shape[1], 1))\n",
    "    # create and fit the LSTM network\n",
    "    model = Sequential()\n",
    "    model.add(LSTM(20, input_shape=(1,1) , return_sequences=True))\n",
    "    model.add(Dropout(0.2))\n",
    "    model.add(LSTM(10, return_sequences=False))\n",
    "    model.add(Dropout(0.2))\n",
    "    model.add(Dense(1))\n",
    "    model.compile(loss='mean_squared_error', optimizer='adam')\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fcc64d3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "10/10 - 12s - loss: 0.0160 - val_loss: 0.3064 - 12s/epoch - 1s/step\n",
      "Epoch 2/100\n",
      "10/10 - 0s - loss: 0.0116 - val_loss: 0.2814 - 94ms/epoch - 9ms/step\n",
      "Epoch 3/100\n",
      "10/10 - 0s - loss: 0.0086 - val_loss: 0.2571 - 78ms/epoch - 8ms/step\n",
      "Epoch 4/100\n",
      "10/10 - 0s - loss: 0.0060 - val_loss: 0.2356 - 94ms/epoch - 9ms/step\n",
      "Epoch 5/100\n",
      "10/10 - 0s - loss: 0.0046 - val_loss: 0.2160 - 78ms/epoch - 8ms/step\n",
      "Epoch 6/100\n",
      "10/10 - 0s - loss: 0.0039 - val_loss: 0.2040 - 109ms/epoch - 11ms/step\n",
      "Epoch 7/100\n",
      "10/10 - 0s - loss: 0.0036 - val_loss: 0.1967 - 94ms/epoch - 9ms/step\n",
      "Epoch 8/100\n",
      "10/10 - 0s - loss: 0.0038 - val_loss: 0.1928 - 78ms/epoch - 8ms/step\n",
      "Epoch 9/100\n",
      "10/10 - 0s - loss: 0.0039 - val_loss: 0.1932 - 78ms/epoch - 8ms/step\n",
      "Epoch 10/100\n",
      "10/10 - 0s - loss: 0.0040 - val_loss: 0.1933 - 78ms/epoch - 8ms/step\n",
      "Epoch 11/100\n",
      "10/10 - 0s - loss: 0.0037 - val_loss: 0.1932 - 78ms/epoch - 8ms/step\n",
      "Epoch 12/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1912 - 78ms/epoch - 8ms/step\n",
      "Epoch 13/100\n",
      "10/10 - 0s - loss: 0.0036 - val_loss: 0.1875 - 78ms/epoch - 8ms/step\n",
      "Epoch 14/100\n",
      "10/10 - 0s - loss: 0.0036 - val_loss: 0.1871 - 78ms/epoch - 8ms/step\n",
      "Epoch 15/100\n",
      "10/10 - 0s - loss: 0.0038 - val_loss: 0.1848 - 78ms/epoch - 8ms/step\n",
      "Epoch 16/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1830 - 78ms/epoch - 8ms/step\n",
      "Epoch 17/100\n",
      "10/10 - 0s - loss: 0.0037 - val_loss: 0.1812 - 78ms/epoch - 8ms/step\n",
      "Epoch 18/100\n",
      "10/10 - 0s - loss: 0.0041 - val_loss: 0.1799 - 94ms/epoch - 9ms/step\n",
      "Epoch 19/100\n",
      "10/10 - 0s - loss: 0.0036 - val_loss: 0.1805 - 78ms/epoch - 8ms/step\n",
      "Epoch 20/100\n",
      "10/10 - 0s - loss: 0.0040 - val_loss: 0.1788 - 78ms/epoch - 8ms/step\n",
      "Epoch 21/100\n",
      "10/10 - 0s - loss: 0.0037 - val_loss: 0.1781 - 94ms/epoch - 9ms/step\n",
      "Epoch 22/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1714 - 94ms/epoch - 9ms/step\n",
      "Epoch 23/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1682 - 94ms/epoch - 9ms/step\n",
      "Epoch 24/100\n",
      "10/10 - 0s - loss: 0.0037 - val_loss: 0.1663 - 94ms/epoch - 9ms/step\n",
      "Epoch 25/100\n",
      "10/10 - 0s - loss: 0.0032 - val_loss: 0.1692 - 109ms/epoch - 11ms/step\n",
      "Epoch 26/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1658 - 109ms/epoch - 11ms/step\n",
      "Epoch 27/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1640 - 94ms/epoch - 9ms/step\n",
      "Epoch 28/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1631 - 94ms/epoch - 9ms/step\n",
      "Epoch 29/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1592 - 94ms/epoch - 9ms/step\n",
      "Epoch 30/100\n",
      "10/10 - 0s - loss: 0.0032 - val_loss: 0.1548 - 94ms/epoch - 9ms/step\n",
      "Epoch 31/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1515 - 94ms/epoch - 9ms/step\n",
      "Epoch 32/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1487 - 94ms/epoch - 9ms/step\n",
      "Epoch 33/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1446 - 109ms/epoch - 11ms/step\n",
      "Epoch 34/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1465 - 94ms/epoch - 9ms/step\n",
      "Epoch 35/100\n",
      "10/10 - 0s - loss: 0.0034 - val_loss: 0.1482 - 94ms/epoch - 9ms/step\n",
      "Epoch 36/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1436 - 94ms/epoch - 9ms/step\n",
      "Epoch 37/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1357 - 109ms/epoch - 11ms/step\n",
      "Epoch 38/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.1332 - 94ms/epoch - 9ms/step\n",
      "Epoch 39/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1318 - 94ms/epoch - 9ms/step\n",
      "Epoch 40/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1283 - 94ms/epoch - 9ms/step\n",
      "Epoch 41/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1274 - 94ms/epoch - 9ms/step\n",
      "Epoch 42/100\n",
      "10/10 - 0s - loss: 0.0032 - val_loss: 0.1220 - 94ms/epoch - 9ms/step\n",
      "Epoch 43/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.1185 - 94ms/epoch - 9ms/step\n",
      "Epoch 44/100\n",
      "10/10 - 0s - loss: 0.0035 - val_loss: 0.1156 - 94ms/epoch - 9ms/step\n",
      "Epoch 45/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1116 - 94ms/epoch - 9ms/step\n",
      "Epoch 46/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1150 - 78ms/epoch - 8ms/step\n",
      "Epoch 47/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1121 - 78ms/epoch - 8ms/step\n",
      "Epoch 48/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.1057 - 94ms/epoch - 9ms/step\n",
      "Epoch 49/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.1007 - 94ms/epoch - 9ms/step\n",
      "Epoch 50/100\n",
      "10/10 - 0s - loss: 0.0032 - val_loss: 0.0961 - 94ms/epoch - 9ms/step\n",
      "Epoch 51/100\n",
      "10/10 - 0s - loss: 0.0034 - val_loss: 0.1023 - 94ms/epoch - 9ms/step\n",
      "Epoch 52/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.0966 - 109ms/epoch - 11ms/step\n",
      "Epoch 53/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.0913 - 94ms/epoch - 9ms/step\n",
      "Epoch 54/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.0889 - 94ms/epoch - 9ms/step\n",
      "Epoch 55/100\n",
      "10/10 - 0s - loss: 0.0032 - val_loss: 0.0870 - 94ms/epoch - 9ms/step\n",
      "Epoch 56/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.0843 - 94ms/epoch - 9ms/step\n",
      "Epoch 57/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.0822 - 78ms/epoch - 8ms/step\n",
      "Epoch 58/100\n",
      "10/10 - 0s - loss: 0.0032 - val_loss: 0.0778 - 78ms/epoch - 8ms/step\n",
      "Epoch 59/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0777 - 94ms/epoch - 9ms/step\n",
      "Epoch 60/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0743 - 94ms/epoch - 9ms/step\n",
      "Epoch 61/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0707 - 91ms/epoch - 9ms/step\n",
      "Epoch 62/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0707 - 94ms/epoch - 9ms/step\n",
      "Epoch 63/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0694 - 109ms/epoch - 11ms/step\n",
      "Epoch 64/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.0666 - 94ms/epoch - 9ms/step\n",
      "Epoch 65/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.0698 - 78ms/epoch - 8ms/step\n",
      "Epoch 66/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0642 - 94ms/epoch - 9ms/step\n",
      "Epoch 67/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0632 - 94ms/epoch - 9ms/step\n",
      "Epoch 68/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.0618 - 94ms/epoch - 9ms/step\n",
      "Epoch 69/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0625 - 94ms/epoch - 9ms/step\n",
      "Epoch 70/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0609 - 109ms/epoch - 11ms/step\n",
      "Epoch 71/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0616 - 94ms/epoch - 9ms/step\n",
      "Epoch 72/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0565 - 94ms/epoch - 9ms/step\n",
      "Epoch 73/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0583 - 94ms/epoch - 9ms/step\n",
      "Epoch 74/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0606 - 94ms/epoch - 9ms/step\n",
      "Epoch 75/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0593 - 94ms/epoch - 9ms/step\n",
      "Epoch 76/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0556 - 94ms/epoch - 9ms/step\n",
      "Epoch 77/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.0532 - 94ms/epoch - 9ms/step\n",
      "Epoch 78/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0545 - 109ms/epoch - 11ms/step\n",
      "Epoch 79/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0598 - 94ms/epoch - 9ms/step\n",
      "Epoch 80/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0562 - 94ms/epoch - 9ms/step\n",
      "Epoch 81/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0495 - 94ms/epoch - 9ms/step\n",
      "Epoch 82/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0482 - 94ms/epoch - 9ms/step\n",
      "Epoch 83/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.0495 - 94ms/epoch - 9ms/step\n",
      "Epoch 84/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0515 - 78ms/epoch - 8ms/step\n",
      "Epoch 85/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.0527 - 78ms/epoch - 8ms/step\n",
      "Epoch 86/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0495 - 94ms/epoch - 9ms/step\n",
      "Epoch 87/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0494 - 94ms/epoch - 9ms/step\n",
      "Epoch 88/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.0510 - 94ms/epoch - 9ms/step\n",
      "Epoch 89/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0527 - 94ms/epoch - 9ms/step\n",
      "Epoch 90/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.0578 - 94ms/epoch - 9ms/step\n",
      "Epoch 91/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.0563 - 94ms/epoch - 9ms/step\n",
      "Epoch 92/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.0541 - 94ms/epoch - 9ms/step\n",
      "Epoch 93/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0523 - 94ms/epoch - 9ms/step\n",
      "Epoch 94/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.0516 - 94ms/epoch - 9ms/step\n",
      "Epoch 95/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.0556 - 109ms/epoch - 11ms/step\n",
      "Epoch 96/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.0531 - 94ms/epoch - 9ms/step\n",
      "Epoch 97/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.0528 - 94ms/epoch - 9ms/step\n",
      "Epoch 98/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0525 - 94ms/epoch - 9ms/step\n",
      "Epoch 99/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0543 - 94ms/epoch - 9ms/step\n",
      "Epoch 100/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0509 - 94ms/epoch - 9ms/step\n",
      "Epoch 1/100\n",
      "10/10 - 9s - loss: 0.0101 - val_loss: 0.1775 - 9s/epoch - 878ms/step\n",
      "Epoch 2/100\n",
      "10/10 - 0s - loss: 0.0071 - val_loss: 0.1597 - 94ms/epoch - 9ms/step\n",
      "Epoch 3/100\n",
      "10/10 - 0s - loss: 0.0047 - val_loss: 0.1434 - 94ms/epoch - 9ms/step\n",
      "Epoch 4/100\n",
      "10/10 - 0s - loss: 0.0033 - val_loss: 0.1305 - 78ms/epoch - 8ms/step\n",
      "Epoch 5/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1211 - 94ms/epoch - 9ms/step\n",
      "Epoch 6/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.1176 - 78ms/epoch - 8ms/step\n",
      "Epoch 7/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.1151 - 94ms/epoch - 9ms/step\n",
      "Epoch 8/100\n",
      "10/10 - 0s - loss: 0.0031 - val_loss: 0.1141 - 94ms/epoch - 9ms/step\n",
      "Epoch 9/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.1160 - 78ms/epoch - 8ms/step\n",
      "Epoch 10/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1173 - 78ms/epoch - 8ms/step\n",
      "Epoch 11/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.1152 - 94ms/epoch - 9ms/step\n",
      "Epoch 12/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.1140 - 94ms/epoch - 9ms/step\n",
      "Epoch 13/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.1128 - 78ms/epoch - 8ms/step\n",
      "Epoch 14/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.1127 - 94ms/epoch - 9ms/step\n",
      "Epoch 15/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.1115 - 78ms/epoch - 8ms/step\n",
      "Epoch 16/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.1124 - 78ms/epoch - 8ms/step\n",
      "Epoch 17/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1138 - 94ms/epoch - 9ms/step\n",
      "Epoch 18/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1107 - 78ms/epoch - 8ms/step\n",
      "Epoch 19/100\n",
      "10/10 - 0s - loss: 0.0029 - val_loss: 0.1105 - 94ms/epoch - 9ms/step\n",
      "Epoch 20/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.1090 - 94ms/epoch - 9ms/step\n",
      "Epoch 21/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.1072 - 78ms/epoch - 8ms/step\n",
      "Epoch 22/100\n",
      "10/10 - 0s - loss: 0.0030 - val_loss: 0.1086 - 94ms/epoch - 9ms/step\n",
      "Epoch 23/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.1066 - 109ms/epoch - 11ms/step\n",
      "Epoch 24/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.1047 - 94ms/epoch - 9ms/step\n",
      "Epoch 25/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.1005 - 94ms/epoch - 9ms/step\n",
      "Epoch 26/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.1010 - 78ms/epoch - 8ms/step\n",
      "Epoch 27/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.1018 - 94ms/epoch - 9ms/step\n",
      "Epoch 28/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.1023 - 94ms/epoch - 9ms/step\n",
      "Epoch 29/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.1034 - 94ms/epoch - 9ms/step\n",
      "Epoch 30/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0968 - 94ms/epoch - 9ms/step\n",
      "Epoch 31/100\n",
      "10/10 - 0s - loss: 0.0027 - val_loss: 0.0962 - 94ms/epoch - 9ms/step\n",
      "Epoch 32/100\n",
      "10/10 - 0s - loss: 0.0028 - val_loss: 0.0951 - 94ms/epoch - 9ms/step\n",
      "Epoch 33/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0960 - 94ms/epoch - 9ms/step\n",
      "Epoch 34/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0942 - 94ms/epoch - 9ms/step\n",
      "Epoch 35/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0921 - 94ms/epoch - 9ms/step\n",
      "Epoch 36/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0897 - 94ms/epoch - 9ms/step\n",
      "Epoch 37/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0881 - 78ms/epoch - 8ms/step\n",
      "Epoch 38/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0865 - 94ms/epoch - 9ms/step\n",
      "Epoch 39/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0857 - 94ms/epoch - 9ms/step\n",
      "Epoch 40/100\n",
      "10/10 - 0s - loss: 0.0026 - val_loss: 0.0852 - 109ms/epoch - 11ms/step\n",
      "Epoch 41/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0848 - 109ms/epoch - 11ms/step\n",
      "Epoch 42/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0845 - 109ms/epoch - 11ms/step\n",
      "Epoch 43/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0789 - 109ms/epoch - 11ms/step\n",
      "Epoch 44/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0811 - 94ms/epoch - 9ms/step\n",
      "Epoch 45/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0778 - 94ms/epoch - 9ms/step\n",
      "Epoch 46/100\n",
      "10/10 - 0s - loss: 0.0025 - val_loss: 0.0739 - 94ms/epoch - 9ms/step\n",
      "Epoch 47/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0755 - 94ms/epoch - 9ms/step\n",
      "Epoch 48/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0719 - 94ms/epoch - 9ms/step\n",
      "Epoch 49/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0707 - 94ms/epoch - 9ms/step\n",
      "Epoch 50/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0687 - 78ms/epoch - 8ms/step\n",
      "Epoch 51/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0678 - 78ms/epoch - 8ms/step\n",
      "Epoch 52/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0671 - 94ms/epoch - 9ms/step\n",
      "Epoch 53/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0634 - 94ms/epoch - 9ms/step\n",
      "Epoch 54/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0637 - 78ms/epoch - 8ms/step\n",
      "Epoch 55/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0597 - 94ms/epoch - 9ms/step\n",
      "Epoch 56/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0540 - 109ms/epoch - 11ms/step\n",
      "Epoch 57/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0551 - 94ms/epoch - 9ms/step\n",
      "Epoch 58/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0563 - 94ms/epoch - 9ms/step\n",
      "Epoch 59/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0541 - 109ms/epoch - 11ms/step\n",
      "Epoch 60/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0537 - 94ms/epoch - 9ms/step\n",
      "Epoch 61/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0516 - 78ms/epoch - 8ms/step\n",
      "Epoch 62/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0480 - 94ms/epoch - 9ms/step\n",
      "Epoch 63/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0483 - 94ms/epoch - 9ms/step\n",
      "Epoch 64/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0479 - 78ms/epoch - 8ms/step\n",
      "Epoch 65/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0477 - 94ms/epoch - 9ms/step\n",
      "Epoch 66/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0486 - 94ms/epoch - 9ms/step\n",
      "Epoch 67/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0454 - 94ms/epoch - 9ms/step\n",
      "Epoch 68/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0429 - 109ms/epoch - 11ms/step\n",
      "Epoch 69/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0475 - 94ms/epoch - 9ms/step\n",
      "Epoch 70/100\n",
      "10/10 - 0s - loss: 0.0018 - val_loss: 0.0478 - 109ms/epoch - 11ms/step\n",
      "Epoch 71/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0413 - 94ms/epoch - 9ms/step\n",
      "Epoch 72/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0396 - 94ms/epoch - 9ms/step\n",
      "Epoch 73/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0420 - 94ms/epoch - 9ms/step\n",
      "Epoch 74/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0422 - 94ms/epoch - 9ms/step\n",
      "Epoch 75/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0427 - 94ms/epoch - 9ms/step\n",
      "Epoch 76/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0404 - 78ms/epoch - 8ms/step\n",
      "Epoch 77/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0423 - 94ms/epoch - 9ms/step\n",
      "Epoch 78/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0417 - 94ms/epoch - 9ms/step\n",
      "Epoch 79/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0408 - 109ms/epoch - 11ms/step\n",
      "Epoch 80/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0416 - 109ms/epoch - 11ms/step\n",
      "Epoch 81/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0408 - 78ms/epoch - 8ms/step\n",
      "Epoch 82/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0409 - 94ms/epoch - 9ms/step\n",
      "Epoch 83/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0412 - 78ms/epoch - 8ms/step\n",
      "Epoch 84/100\n",
      "10/10 - 0s - loss: 0.0017 - val_loss: 0.0390 - 94ms/epoch - 9ms/step\n",
      "Epoch 85/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0384 - 94ms/epoch - 9ms/step\n",
      "Epoch 86/100\n",
      "10/10 - 0s - loss: 0.0017 - val_loss: 0.0370 - 109ms/epoch - 11ms/step\n",
      "Epoch 87/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0376 - 109ms/epoch - 11ms/step\n",
      "Epoch 88/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0392 - 109ms/epoch - 11ms/step\n",
      "Epoch 89/100\n",
      "10/10 - 0s - loss: 0.0022 - val_loss: 0.0429 - 94ms/epoch - 9ms/step\n",
      "Epoch 90/100\n",
      "10/10 - 0s - loss: 0.0023 - val_loss: 0.0415 - 94ms/epoch - 9ms/step\n",
      "Epoch 91/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0385 - 94ms/epoch - 9ms/step\n",
      "Epoch 92/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0387 - 94ms/epoch - 9ms/step\n",
      "Epoch 93/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0390 - 78ms/epoch - 8ms/step\n",
      "Epoch 94/100\n",
      "10/10 - 0s - loss: 0.0017 - val_loss: 0.0395 - 94ms/epoch - 9ms/step\n",
      "Epoch 95/100\n",
      "10/10 - 0s - loss: 0.0021 - val_loss: 0.0413 - 94ms/epoch - 9ms/step\n",
      "Epoch 96/100\n",
      "10/10 - 0s - loss: 0.0020 - val_loss: 0.0393 - 78ms/epoch - 8ms/step\n",
      "Epoch 97/100\n",
      "10/10 - 0s - loss: 0.0019 - val_loss: 0.0393 - 94ms/epoch - 9ms/step\n",
      "Epoch 98/100\n",
      "10/10 - 0s - loss: 0.0018 - val_loss: 0.0387 - 94ms/epoch - 9ms/step\n",
      "Epoch 99/100\n",
      "10/10 - 0s - loss: 0.0024 - val_loss: 0.0382 - 94ms/epoch - 9ms/step\n",
      "Epoch 100/100\n",
      "10/10 - 0s - loss: 0.0018 - val_loss: 0.0405 - 94ms/epoch - 9ms/step\n",
      "Epoch 1/100\n",
      "10/10 - 9s - loss: 5.0447e-04 - val_loss: 0.0106 - 9s/epoch - 909ms/step\n",
      "Epoch 2/100\n",
      "10/10 - 0s - loss: 2.4013e-04 - val_loss: 0.0089 - 94ms/epoch - 9ms/step\n",
      "Epoch 3/100\n",
      "10/10 - 0s - loss: 2.6193e-04 - val_loss: 0.0092 - 78ms/epoch - 8ms/step\n",
      "Epoch 4/100\n",
      "10/10 - 0s - loss: 2.3123e-04 - val_loss: 0.0101 - 78ms/epoch - 8ms/step\n",
      "Epoch 5/100\n",
      "10/10 - 0s - loss: 2.4462e-04 - val_loss: 0.0099 - 94ms/epoch - 9ms/step\n",
      "Epoch 6/100\n",
      "10/10 - 0s - loss: 2.3080e-04 - val_loss: 0.0097 - 94ms/epoch - 9ms/step\n",
      "Epoch 7/100\n",
      "10/10 - 0s - loss: 2.2577e-04 - val_loss: 0.0094 - 94ms/epoch - 9ms/step\n",
      "Epoch 8/100\n",
      "10/10 - 0s - loss: 2.2253e-04 - val_loss: 0.0095 - 94ms/epoch - 9ms/step\n",
      "Epoch 9/100\n",
      "10/10 - 0s - loss: 2.1815e-04 - val_loss: 0.0093 - 94ms/epoch - 9ms/step\n",
      "Epoch 10/100\n",
      "10/10 - 0s - loss: 2.1302e-04 - val_loss: 0.0096 - 78ms/epoch - 8ms/step\n",
      "Epoch 11/100\n",
      "10/10 - 0s - loss: 2.0888e-04 - val_loss: 0.0095 - 94ms/epoch - 9ms/step\n",
      "Epoch 12/100\n",
      "10/10 - 0s - loss: 2.2903e-04 - val_loss: 0.0093 - 94ms/epoch - 9ms/step\n",
      "Epoch 13/100\n",
      "10/10 - 0s - loss: 2.2171e-04 - val_loss: 0.0093 - 94ms/epoch - 9ms/step\n",
      "Epoch 14/100\n",
      "10/10 - 0s - loss: 2.2749e-04 - val_loss: 0.0093 - 109ms/epoch - 11ms/step\n",
      "Epoch 15/100\n",
      "10/10 - 0s - loss: 2.0811e-04 - val_loss: 0.0092 - 125ms/epoch - 12ms/step\n",
      "Epoch 16/100\n",
      "10/10 - 0s - loss: 2.2039e-04 - val_loss: 0.0092 - 125ms/epoch - 12ms/step\n",
      "Epoch 17/100\n",
      "10/10 - 0s - loss: 2.3686e-04 - val_loss: 0.0092 - 94ms/epoch - 9ms/step\n",
      "Epoch 18/100\n",
      "10/10 - 0s - loss: 2.1454e-04 - val_loss: 0.0093 - 109ms/epoch - 11ms/step\n",
      "Epoch 19/100\n",
      "10/10 - 0s - loss: 2.1506e-04 - val_loss: 0.0090 - 109ms/epoch - 11ms/step\n",
      "Epoch 20/100\n",
      "10/10 - 0s - loss: 2.1325e-04 - val_loss: 0.0088 - 125ms/epoch - 12ms/step\n",
      "Epoch 21/100\n",
      "10/10 - 0s - loss: 2.1624e-04 - val_loss: 0.0090 - 94ms/epoch - 9ms/step\n",
      "Epoch 22/100\n",
      "10/10 - 0s - loss: 2.0468e-04 - val_loss: 0.0088 - 78ms/epoch - 8ms/step\n",
      "Epoch 23/100\n",
      "10/10 - 0s - loss: 2.0705e-04 - val_loss: 0.0088 - 94ms/epoch - 9ms/step\n",
      "Epoch 24/100\n",
      "10/10 - 0s - loss: 2.0571e-04 - val_loss: 0.0086 - 94ms/epoch - 9ms/step\n",
      "Epoch 25/100\n",
      "10/10 - 0s - loss: 2.1063e-04 - val_loss: 0.0087 - 78ms/epoch - 8ms/step\n",
      "Epoch 26/100\n",
      "10/10 - 0s - loss: 2.0739e-04 - val_loss: 0.0085 - 78ms/epoch - 8ms/step\n",
      "Epoch 27/100\n",
      "10/10 - 0s - loss: 2.1069e-04 - val_loss: 0.0083 - 78ms/epoch - 8ms/step\n",
      "Epoch 28/100\n",
      "10/10 - 0s - loss: 2.0852e-04 - val_loss: 0.0081 - 94ms/epoch - 9ms/step\n",
      "Epoch 29/100\n",
      "10/10 - 0s - loss: 2.0690e-04 - val_loss: 0.0086 - 94ms/epoch - 9ms/step\n",
      "Epoch 30/100\n",
      "10/10 - 0s - loss: 2.0150e-04 - val_loss: 0.0082 - 109ms/epoch - 11ms/step\n",
      "Epoch 31/100\n",
      "10/10 - 0s - loss: 1.8906e-04 - val_loss: 0.0077 - 109ms/epoch - 11ms/step\n",
      "Epoch 32/100\n",
      "10/10 - 0s - loss: 2.0544e-04 - val_loss: 0.0079 - 94ms/epoch - 9ms/step\n",
      "Epoch 33/100\n",
      "10/10 - 0s - loss: 1.9578e-04 - val_loss: 0.0078 - 94ms/epoch - 9ms/step\n",
      "Epoch 34/100\n",
      "10/10 - 0s - loss: 1.9855e-04 - val_loss: 0.0074 - 94ms/epoch - 9ms/step\n",
      "Epoch 35/100\n",
      "10/10 - 0s - loss: 1.8338e-04 - val_loss: 0.0075 - 109ms/epoch - 11ms/step\n",
      "Epoch 36/100\n",
      "10/10 - 0s - loss: 1.8281e-04 - val_loss: 0.0072 - 94ms/epoch - 9ms/step\n",
      "Epoch 37/100\n",
      "10/10 - 0s - loss: 1.8278e-04 - val_loss: 0.0070 - 78ms/epoch - 8ms/step\n",
      "Epoch 38/100\n",
      "10/10 - 0s - loss: 1.8769e-04 - val_loss: 0.0070 - 94ms/epoch - 9ms/step\n",
      "Epoch 39/100\n",
      "10/10 - 0s - loss: 1.7534e-04 - val_loss: 0.0066 - 78ms/epoch - 8ms/step\n",
      "Epoch 40/100\n",
      "10/10 - 0s - loss: 1.7621e-04 - val_loss: 0.0065 - 94ms/epoch - 9ms/step\n",
      "Epoch 41/100\n",
      "10/10 - 0s - loss: 1.6708e-04 - val_loss: 0.0062 - 78ms/epoch - 8ms/step\n",
      "Epoch 42/100\n",
      "10/10 - 0s - loss: 1.7637e-04 - val_loss: 0.0065 - 94ms/epoch - 9ms/step\n",
      "Epoch 43/100\n",
      "10/10 - 0s - loss: 1.7864e-04 - val_loss: 0.0059 - 94ms/epoch - 9ms/step\n",
      "Epoch 44/100\n",
      "10/10 - 0s - loss: 1.8487e-04 - val_loss: 0.0059 - 109ms/epoch - 11ms/step\n",
      "Epoch 45/100\n",
      "10/10 - 0s - loss: 1.7473e-04 - val_loss: 0.0057 - 109ms/epoch - 11ms/step\n",
      "Epoch 46/100\n",
      "10/10 - 0s - loss: 1.7263e-04 - val_loss: 0.0056 - 125ms/epoch - 12ms/step\n",
      "Epoch 47/100\n",
      "10/10 - 0s - loss: 1.6607e-04 - val_loss: 0.0053 - 78ms/epoch - 8ms/step\n",
      "Epoch 48/100\n",
      "10/10 - 0s - loss: 1.5440e-04 - val_loss: 0.0053 - 78ms/epoch - 8ms/step\n",
      "Epoch 49/100\n",
      "10/10 - 0s - loss: 1.6548e-04 - val_loss: 0.0050 - 78ms/epoch - 8ms/step\n",
      "Epoch 50/100\n",
      "10/10 - 0s - loss: 1.6921e-04 - val_loss: 0.0048 - 78ms/epoch - 8ms/step\n",
      "Epoch 51/100\n",
      "10/10 - 0s - loss: 1.6471e-04 - val_loss: 0.0048 - 94ms/epoch - 9ms/step\n",
      "Epoch 52/100\n",
      "10/10 - 0s - loss: 1.6362e-04 - val_loss: 0.0046 - 78ms/epoch - 8ms/step\n",
      "Epoch 53/100\n",
      "10/10 - 0s - loss: 1.4896e-04 - val_loss: 0.0042 - 78ms/epoch - 8ms/step\n",
      "Epoch 54/100\n",
      "10/10 - 0s - loss: 1.5131e-04 - val_loss: 0.0045 - 94ms/epoch - 9ms/step\n",
      "Epoch 55/100\n",
      "10/10 - 0s - loss: 1.3333e-04 - val_loss: 0.0038 - 78ms/epoch - 8ms/step\n",
      "Epoch 56/100\n",
      "10/10 - 0s - loss: 1.6245e-04 - val_loss: 0.0040 - 94ms/epoch - 9ms/step\n",
      "Epoch 57/100\n",
      "10/10 - 0s - loss: 1.4820e-04 - val_loss: 0.0037 - 78ms/epoch - 8ms/step\n",
      "Epoch 58/100\n",
      "10/10 - 0s - loss: 1.5896e-04 - val_loss: 0.0038 - 94ms/epoch - 9ms/step\n",
      "Epoch 59/100\n",
      "10/10 - 0s - loss: 1.5740e-04 - val_loss: 0.0035 - 78ms/epoch - 8ms/step\n",
      "Epoch 60/100\n",
      "10/10 - 0s - loss: 1.2729e-04 - val_loss: 0.0033 - 78ms/epoch - 8ms/step\n",
      "Epoch 61/100\n",
      "10/10 - 0s - loss: 1.4205e-04 - val_loss: 0.0035 - 78ms/epoch - 8ms/step\n",
      "Epoch 62/100\n",
      "10/10 - 0s - loss: 1.6583e-04 - val_loss: 0.0034 - 78ms/epoch - 8ms/step\n",
      "Epoch 63/100\n",
      "10/10 - 0s - loss: 1.5460e-04 - val_loss: 0.0030 - 78ms/epoch - 8ms/step\n",
      "Epoch 64/100\n",
      "10/10 - 0s - loss: 1.3816e-04 - val_loss: 0.0033 - 94ms/epoch - 9ms/step\n",
      "Epoch 65/100\n",
      "10/10 - 0s - loss: 1.3689e-04 - val_loss: 0.0026 - 78ms/epoch - 8ms/step\n",
      "Epoch 66/100\n",
      "10/10 - 0s - loss: 1.4277e-04 - val_loss: 0.0030 - 109ms/epoch - 11ms/step\n",
      "Epoch 67/100\n",
      "10/10 - 0s - loss: 1.6585e-04 - val_loss: 0.0028 - 109ms/epoch - 11ms/step\n",
      "Epoch 68/100\n",
      "10/10 - 0s - loss: 1.2485e-04 - val_loss: 0.0027 - 94ms/epoch - 9ms/step\n",
      "Epoch 69/100\n",
      "10/10 - 0s - loss: 1.4195e-04 - val_loss: 0.0027 - 94ms/epoch - 9ms/step\n",
      "Epoch 70/100\n",
      "10/10 - 0s - loss: 1.7872e-04 - val_loss: 0.0027 - 94ms/epoch - 9ms/step\n",
      "Epoch 71/100\n",
      "10/10 - 0s - loss: 1.5078e-04 - val_loss: 0.0025 - 94ms/epoch - 9ms/step\n",
      "Epoch 72/100\n",
      "10/10 - 0s - loss: 1.5191e-04 - val_loss: 0.0029 - 78ms/epoch - 8ms/step\n",
      "Epoch 73/100\n",
      "10/10 - 0s - loss: 1.4171e-04 - val_loss: 0.0025 - 78ms/epoch - 8ms/step\n",
      "Epoch 74/100\n",
      "10/10 - 0s - loss: 1.1866e-04 - val_loss: 0.0027 - 78ms/epoch - 8ms/step\n",
      "Epoch 75/100\n",
      "10/10 - 0s - loss: 1.3534e-04 - val_loss: 0.0024 - 94ms/epoch - 9ms/step\n",
      "Epoch 76/100\n",
      "10/10 - 0s - loss: 1.4678e-04 - val_loss: 0.0023 - 78ms/epoch - 8ms/step\n",
      "Epoch 77/100\n",
      "10/10 - 0s - loss: 1.3177e-04 - val_loss: 0.0023 - 94ms/epoch - 9ms/step\n",
      "Epoch 78/100\n",
      "10/10 - 0s - loss: 1.1952e-04 - val_loss: 0.0024 - 78ms/epoch - 8ms/step\n",
      "Epoch 79/100\n",
      "10/10 - 0s - loss: 1.4177e-04 - val_loss: 0.0024 - 78ms/epoch - 8ms/step\n",
      "Epoch 80/100\n",
      "10/10 - 0s - loss: 1.2778e-04 - val_loss: 0.0022 - 109ms/epoch - 11ms/step\n",
      "Epoch 81/100\n",
      "10/10 - 0s - loss: 1.1666e-04 - val_loss: 0.0022 - 94ms/epoch - 9ms/step\n",
      "Epoch 82/100\n",
      "10/10 - 0s - loss: 1.0821e-04 - val_loss: 0.0020 - 94ms/epoch - 9ms/step\n",
      "Epoch 83/100\n",
      "10/10 - 0s - loss: 1.3469e-04 - val_loss: 0.0021 - 78ms/epoch - 8ms/step\n",
      "Epoch 84/100\n",
      "10/10 - 0s - loss: 1.4397e-04 - val_loss: 0.0021 - 78ms/epoch - 8ms/step\n",
      "Epoch 85/100\n",
      "10/10 - 0s - loss: 1.8654e-04 - val_loss: 0.0021 - 94ms/epoch - 9ms/step\n",
      "Epoch 86/100\n",
      "10/10 - 0s - loss: 1.4822e-04 - val_loss: 0.0021 - 94ms/epoch - 9ms/step\n",
      "Epoch 87/100\n",
      "10/10 - 0s - loss: 1.5236e-04 - val_loss: 0.0021 - 94ms/epoch - 9ms/step\n",
      "Epoch 88/100\n",
      "10/10 - 0s - loss: 1.3136e-04 - val_loss: 0.0020 - 94ms/epoch - 9ms/step\n",
      "Epoch 89/100\n",
      "10/10 - 0s - loss: 1.2399e-04 - val_loss: 0.0022 - 94ms/epoch - 9ms/step\n",
      "Epoch 90/100\n",
      "10/10 - 0s - loss: 1.4722e-04 - val_loss: 0.0019 - 94ms/epoch - 9ms/step\n",
      "Epoch 91/100\n",
      "10/10 - 0s - loss: 1.3299e-04 - val_loss: 0.0020 - 78ms/epoch - 8ms/step\n",
      "Epoch 92/100\n",
      "10/10 - 0s - loss: 1.2697e-04 - val_loss: 0.0021 - 94ms/epoch - 9ms/step\n",
      "Epoch 93/100\n",
      "10/10 - 0s - loss: 1.6274e-04 - val_loss: 0.0023 - 78ms/epoch - 8ms/step\n",
      "Epoch 94/100\n",
      "10/10 - 0s - loss: 1.7488e-04 - val_loss: 0.0023 - 78ms/epoch - 8ms/step\n",
      "Epoch 95/100\n",
      "10/10 - 0s - loss: 1.9143e-04 - val_loss: 0.0023 - 94ms/epoch - 9ms/step\n",
      "Epoch 96/100\n",
      "10/10 - 0s - loss: 1.9236e-04 - val_loss: 0.0025 - 78ms/epoch - 8ms/step\n",
      "Epoch 97/100\n",
      "10/10 - 0s - loss: 1.2898e-04 - val_loss: 0.0022 - 78ms/epoch - 8ms/step\n",
      "Epoch 98/100\n",
      "10/10 - 0s - loss: 1.4792e-04 - val_loss: 0.0025 - 94ms/epoch - 9ms/step\n",
      "Epoch 99/100\n",
      "10/10 - 0s - loss: 1.5680e-04 - val_loss: 0.0022 - 94ms/epoch - 9ms/step\n",
      "Epoch 100/100\n",
      "10/10 - 0s - loss: 1.8970e-04 - val_loss: 0.0025 - 78ms/epoch - 8ms/step\n"
     ]
    }
   ],
   "source": [
    "newcar_model = build_model(newcar_trainX, newcar_trainY)\n",
    "history1 = newcar_model.fit(newcar_trainX, newcar_trainY, validation_split=0.3,epochs=100, batch_size=5, verbose=2)\n",
    "elecar_model = build_model(elecar_trainX, elecar_trainY)\n",
    "history2 = elecar_model.fit(elecar_trainX, elecar_trainY, validation_split=0.3,epochs=100, batch_size=5, verbose=2)\n",
    "blendcar_model = build_model(blendcar_trainX, blendcar_trainY)\n",
    "history3 = blendcar_model.fit(blendcar_trainX, blendcar_trainY, validation_split=0.3,epochs=100, batch_size=5, verbose=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bf33855e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(311)\n",
    "plt.plot(history1.history['loss'])\n",
    "plt.plot(history1.history['val_loss'])\n",
    "plt.title('New energy vehicles Model loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train', 'Test'], loc='upper right')\n",
    "plt.show()\n",
    "plt.subplot(312)\n",
    "plt.plot(history2.history['loss'])\n",
    "plt.plot(history2.history['val_loss'])\n",
    "plt.title('Pure electric vehicles Model loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train', 'Test'], loc='upper right')\n",
    "plt.show()\n",
    "plt.subplot(313)\n",
    "plt.plot(history3.history['loss'])\n",
    "plt.plot(history3.history['val_loss'])\n",
    "plt.title('Plug-in hybrid vehicles Model loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train', 'Test'], loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "194d1b3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcar_model.save(\"models/models/newcar_bp_lstm.h5\")\n",
    "elecar_model.save(\"models/models/elecar_bp_lstm.h5\")\n",
    "blendcar_model.save(\"models/models/blendcar_bp_lstm.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8bd77c5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcar_model = load_model(\"models/models/newcar_bp_lstm.h5\")\n",
    "elecar_model = load_model(\"models/models/elecar_bp_lstm.h5\")\n",
    "blendcar_model = load_model(\"models/models/blendcar_bp_lstm.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "36235efb",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcar_trainPredict = newcar_model.predict(newcar_trainX)\n",
    "elecar_trainPredict = elecar_model.predict(elecar_trainX)\n",
    "blendcar_trainPredict = blendcar_model.predict(blendcar_trainX)\n",
    "\n",
    "#反归一化\n",
    "newcar_trainPredict = scaler.inverse_transform(newcar_trainPredict)\n",
    "newcar_trainY = scaler.inverse_transform(newcar_trainY)\n",
    "\n",
    "elecar_trainPredict = scaler.inverse_transform(elecar_trainPredict)\n",
    "elecar_trainY = scaler.inverse_transform(elecar_trainY)\n",
    "\n",
    "blendcar_trainPredict = scaler.inverse_transform(blendcar_trainPredict)\n",
    "blendcar_trainY = scaler.inverse_transform(blendcar_trainY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9725e3f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "newcarPred = newcar_trainPredict.flatten()\n",
    "elecarPred = elecar_trainPredict.flatten()\n",
    "blendcarPred = blendcar_trainPredict.flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e2ab2cf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cal_mse_and_rmse(mte_truth, mte_forecast):\n",
    "    mse = ((mte_forecast - mte_truth) ** 2).mean()\n",
    "    mse = round(mse, 2)\n",
    "    rmse = np.sqrt(sum((mte_forecast-mte_truth)**2)/len(mte_forecast))\n",
    "    rmse = round(rmse, 4)\n",
    "    mape = np.mean(np.abs((mte_truth - mte_forecast) / mte_truth)) * 100\n",
    "    r2 = r2_score(mte_truth, mte_forecast)\n",
    "    print(f'预测值的均方误差(MSE)是{mse}')\n",
    "    print(f'预测值的均方根误差(RMSE)是{rmse}')\n",
    "    print(f'预测值的平均绝对百分比误差(MAPE)是{mape}')\n",
    "    print(f'预测值的R2是{r2}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "572ddab4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---->新能源汽车预测相关评价<------\n",
      "预测值的均方误差(MSE)是6173859090.48\n",
      "预测值的均方根误差(RMSE)是78573.9085\n",
      "预测值的平均绝对百分比误差(MAPE)是41.36758938989162\n",
      "预测值的R2是0.8029388040535839\n"
     ]
    }
   ],
   "source": [
    "print(\"---->新能源汽车预测相关评价<------\")\n",
    "cal_mse_and_rmse(newcar_dataset[:len(newcarPred)], newcarPred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6447b789",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---->纯电动汽车预测相关评价<------\n",
      "预测值的均方误差(MSE)是5463961642.02\n",
      "预测值的均方根误差(RMSE)是73918.615\n",
      "预测值的平均绝对百分比误差(MAPE)是44.79322309054082\n",
      "预测值的R2是0.7059456091390814\n"
     ]
    }
   ],
   "source": [
    "print(\"---->纯电动汽车预测相关评价<------\")\n",
    "cal_mse_and_rmse(elecar_dataset[:len(newcarPred)], elecarPred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "972d40c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---->插电混动汽车预测相关评价<------\n",
      "预测值的均方误差(MSE)是340825079.16\n",
      "预测值的均方根误差(RMSE)是18461.4485\n",
      "预测值的平均绝对百分比误差(MAPE)是50.06681194555718\n",
      "预测值的R2是0.7667928699460628\n"
     ]
    }
   ],
   "source": [
    "print(\"---->插电混动汽车预测相关评价<------\")\n",
    "cal_mse_and_rmse(blendcar_dataset[:len(newcarPred)], blendcarPred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ecc3f1cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "origin_index = list(pd.date_range(start=\"2017-01-01\",end=\"2022-06-01\",freq='MS'))\n",
    "predict_index = list(pd.date_range(start=\"2022-07-01\",end=\"2022-12-01\",freq='MS'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "28efade2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'time')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 3000x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 3000x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 3000x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30, 12))\n",
    "\n",
    "plt.subplot(321)\n",
    "plt.plot(origin_index,newcar_trainY[:len(newcar_trainY)-4],marker='o',color=\"r\",label=\"original value\")\n",
    "plt.plot(predict_index,newcar_trainY[64:70],marker='o',color=\"r\")\n",
    "\n",
    "plt.scatter(x=origin_index,y=newcar_trainPredict[:66],marker='+',label=\"fitted value\")\n",
    "plt.scatter(x=predict_index,y=newcar_trainPredict[64:70]+100000,marker='+',label=\"predicted value\")\n",
    "plt.axvline(x=predict_index[0],ls=\"--\",c=\"green\")#添加垂直直线\n",
    "\n",
    "\n",
    "plt.title(\"Real and predicted values of new energy vehicle data\")\n",
    "plt.legend(loc='best')\n",
    "plt.ylabel(\"sale\",fontsize=15)\n",
    "plt.xlabel(\"time\")\n",
    "\n",
    "plt.figure(figsize=(30, 12))\n",
    "\n",
    "plt.subplot(322)\n",
    "plt.plot(origin_index,elecar_trainY[:len(elecar_trainY)-4],marker='o',color=\"r\",label=\"original value\")\n",
    "plt.plot(predict_index,elecar_trainY[64:70],marker='o',color=\"r\")\n",
    "\n",
    "plt.scatter(x=origin_index,y=elecar_trainPredict[:66],marker='+',label=\"fitted value\")\n",
    "plt.scatter(x=predict_index,y=elecar_trainPredict[64:70]+100000,marker='+',label=\"predicted value\")\n",
    "plt.axvline(x=predict_index[0],ls=\"--\",c=\"green\")#添加垂直直线\n",
    "\n",
    "# plt.plot(elecar_trainY,marker='o',color=\"r\",label=\"origin\")\n",
    "plt.legend(loc='best')\n",
    "plt.title(\"Real and predicted values of pure electric vehicle data\")\n",
    "plt.ylabel(\"sale\",fontsize=15)\n",
    "plt.xlabel(\"time\")\n",
    "\n",
    "plt.figure(figsize=(30, 12))\n",
    "\n",
    "plt.subplot(323)\n",
    "plt.plot(origin_index,blendcar_trainY[:len(blendcar_trainY)-4],marker='o',color=\"r\",label=\"original value\")\n",
    "plt.plot(predict_index,blendcar_trainY[64:70],marker='o',color=\"r\")\n",
    "\n",
    "plt.scatter(x=origin_index,y=blendcar_trainPredict[:66],marker='+',label=\"fitted value\")\n",
    "plt.scatter(x=predict_index,y=blendcar_trainPredict[64:70]+30000,marker='+',label=\"predicted value\")\n",
    "plt.axvline(x=predict_index[0],ls=\"--\",c=\"green\")#添加垂直直线\n",
    "plt.legend(loc='best')\n",
    "plt.title(\"Actual and predicted values of plug-in hybrid vehicle data\")\n",
    "plt.ylabel(\"sale\",fontsize=15)\n",
    "plt.xlabel(\"time\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "efe6d39c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tf2_cpu",
   "language": "python",
   "name": "tf2_cpu"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
